Radar terrain contour matching and positioning method

Abstract

The invention provides a radar terrain contour matching and positioning method, which comprises the following steps of: firstly, carrying out single-elevation delay extraction processing on imaging result information, and carrying out elevation gradient information extraction of a continuous elevation contour; performing continuous equal-height point set search based on the elevation gradient information of the continuous elevation profile and prior information to obtain equal-height point set position information, and performing comprehensive fitting calculation; when the loss amount of the coordinate difference between the equal-height point group position information and the initial reference position information is minimum, regarding the corresponding equal-height point group position as a new initial position; and performing iterative judgment based on the new initial position and outputting a target position. According to the embodiment, the projection points of the result point set are selected as position information, so that the method is suitable for aircraft wide-beam radar terrain contour matching work, the problem of low operation efficiency of an aircraft positioning algorithm under the condition of poor satellite signals can be solved, and the positioning accuracy is improved. Therefore, a quick and accurate self-positioning function under the condition that satellite signals are cut off or the signals are poor is realized.

Description

Technical Field

[0001] The invention relates to the field of autonomous matching and positioning of aircraft wide-beam radars, and in particular to a radar terrain profile matching and positioning method. Background Art

[0002] The reliability of matching positioning is the key to the engineering application of matching positioning technology. How to adapt to the positioning environment in the matching algorithm and the reliability of the method in extreme environments are major challenges of matching positioning technology. Based on the current situation, traditional algorithm designs are all aimed at the positioning needs of underwater vehicles, have poor adaptability to the platform's motion state, and have a high amount of calculations; most traditional matching methods use traversal matching methods. Although the traversal matching method has a simple algorithm, it has low computational efficiency, the calculation process is too mechanical, and the positioning accuracy depends on the traversal density.

[0003] At present, traditional aircraft positioning methods rely on satellite signal information. When the satellite signal is cut off or the signal is poor, the positioning algorithm has low operating efficiency. Summary of the invention

[0004] The embodiment of the present invention provides a radar terrain profile matching and positioning method, aiming to provide an efficient and intelligent wide-beam radar terrain profile matching and positioning method to improve the autonomous positioning function.

[0005] In a first aspect, an embodiment of the present invention provides a radar terrain profile matching and positioning method, the method comprising the following steps: The wide beam of the radar is irradiated toward the three-dimensional terrain to obtain the imaging result information of the delayed Doppler map, and the Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and the elevation gradient information of the continuous elevation contour is extracted; Taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation profile and the prior information to obtain contour point group position information; the contour point group position information and the initial reference position information are comprehensively fitted and calculated; When the coordinate difference loss between the contour point group position information and the initial reference position information is minimized, the contour point group position corresponding to the time when the coordinate difference loss is minimized is regarded as the new initial position; based on the new initial position, the next round of continuous contour point set search and iterative judgment of comprehensive fitting calculation is performed, and when the iterative judgment reaches the iteration termination condition, the target position is output.

[0006] Optionally, the Brownian model expression is as follows:

[0007] represents the Brownian model, where represents the planar impulse response of the delay-Doppler map, Indicates echo delay, which means the time it takes for a signal to be transmitted and received. represents the frequency of the delay-Doppler map, It describes the scattering characteristics of the detection surface when the altimeter echo is nearly vertically illuminated by integrating a specified function on a circle. The probability density function of the plane scattering intensity representing the delay-Doppler map, represents the transmission probability of the delay-Doppler map.

[0008] Optionally, the The expression is as follows:

[0009] in, Indicates the echo delay, represents the plane spatial position of the delay Doppler map, represents the amplitude value of the delay Doppler image, represents the exponential term of the delay-Doppler map, The function representing the delay-Doppler map, represents the difference term of the delay-Doppler map.

[0010] Optionally, the The expression is as follows:

[0011] in, Indicates the echo delay, represents the standard deviation, , represents the average value, Represents the speed of light.

[0012] Optionally, the The expression is as follows:

[0013] in, Indicates the echo delay, is the sampling period, is the altimeter receiving bandwidth, To delay the acquisition time of the Doppler image, represents the frequency of the delay-Doppler map, is the sampling frequency.

[0014] Optionally, the Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and to extract elevation gradient information of continuous elevation contours, specifically: The posterior probability is constructed using the Bayesian expression, and the expected value of the posterior probability is calculated to obtain the echo delay. Estimated results; is the echo delay, which indicates the time from signal transmission to reception. The corresponding terrain height is calculated according to the echo delay to obtain the single elevation delay extraction processing result; Accumulate the results of multiple single elevation delay extraction processes to obtain continuous elevation contour elevation values; The obtained continuous elevation profile elevation values ​​are averaged to obtain the elevation mean of the continuous elevation profile, and then the elevation mean is subtracted from the continuous elevation profile elevation value to obtain the elevation gradient information of the continuous elevation profile.

[0015] Optionally, taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the prior information, specifically including: Get the pre-selected digital elevation map of the current flight area in advance; Delimiting the preselected digital elevation map, adjusting the delimited range accordingly according to the initial position and the irradiated area; taking the endpoint of the irradiated area as a reference position, determining an extended area of ​​a preset size as the preselected range of the area, and completing the delimitation of the preselected area of ​​the current area; Based on the preselected area, extracting the elevation gradient information of the digital elevation map of the preselected area, that is, obtaining the prior information; The continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the elevation gradient information of the preselected area to obtain the contour point group information.

[0016] Optionally, the position information of the contour point group includes the center position of the point set and the coordinate difference between each point and the center, wherein the coordinate difference between each point and the center is expressed as: ,

[0017] in, is the iso-height point of the delay-Doppler map, is the initial reference position of the delay Doppler map, are the center coordinates of the isoheight points of the delay-Doppler map, is the center coordinate of the initial reference position of the delay Doppler map, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

[0018] Optionally, the continuous search of the iso-height point set follows the Euclidean distance and minimum principle. The Euclidean distance and expression are as follows:

[0019] In the formula, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation, including rotation and translation transformation , is the total number of points;

[0020] in, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation translation, is the rigid transformation rotation, The total number of points.

[0021] Optionally, the Euclidean distance expression is as follows:

[0022] in, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

[0023] In an embodiment of the present application, imaging result information of a delayed Doppler map is obtained. This embodiment combines the echo characteristics of a wide-beam detection radar with the flight operation environment of an aircraft, adopts a Brownian model with a Bayesian estimation method parameter fitting method, extracts terrain contour features, and based on the obtained continuous elevation contour information, cooperates with the digital elevation map prior information, performs a continuous selection search for the nearest contour point with the single elevation point at the initial position as the center of the circle, obtains contour point group position information, and performs a comprehensive fitting operation on the contour point group position information and the initial position information, regards the contour point group position corresponding to the minimum coordinate difference loss as the new initial position for iterative judgment, performs the next round of continuous contour point set search and iterative judgment of the comprehensive fitting calculation, and outputs the iterative result when the iterative judgment reaches the iteration termination condition.

[0024] This application selects the projection points of the result point set as the position information, making it suitable for the aircraft wide-beam radar terrain contour matching work, which can solve the problem that the traditional aircraft positioning method relies on satellite signal information and the positioning algorithm has low operating efficiency when the satellite signal is cut off or the signal is poor, thereby realizing a fast and accurate autonomous positioning function when the satellite signal is cut off or the signal is poor. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 is a flow chart of a radar terrain contour matching and positioning method provided by an embodiment of the present invention; Figure 2 is a specific implementation flow chart of the radar terrain profile matching and positioning method provided by an embodiment of the present invention; Figure 3 is a model diagram of the radar terrain contour matching and positioning method provided by an embodiment of the present invention; Figure 4 is a Brownian model signal diagram provided by an embodiment of the present invention; Figure 5 is a schematic diagram of preselection of a matching area provided by an embodiment of the present invention; Figure 6 is a schematic diagram of matching positioning provided by an embodiment of the present invention; Figure 7 is a simulated terrain scene map provided by an embodiment of the present invention; Figure 8 is a delay Doppler map provided by an embodiment of the present invention; Fig. 9 is an elevation extraction result map provided by an embodiment of the present invention; Fig.10 This is a matching positioning result diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] like Figure 1As shown, Figure 1 1 is a flow chart of a radar terrain contour matching and positioning method provided by an embodiment of the present invention, and the radar terrain contour matching and positioning method comprises steps 101 to 104: Step 101, the radar wide beam is irradiated toward the three-dimensional terrain to obtain the imaging result information of the delayed Doppler map, the Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and the elevation gradient information of the continuous elevation profile is extracted.

[0029] In the embodiment of the present invention, after the radar altimeter receives the backscattered signal from the ground, it will obtain a processed delay Doppler map after full de-skewing, intermediate frequency filtering, FFT transformation, etc. The delay of the delay Doppler map corresponds to the height between the aircraft and the ground. The above delay Doppler map (Delay·Doppler Map, DDM) includes the delay and Doppler information of the target.

[0030] The above Bayesian estimation method is a probabilistic statistical method, which calculates the best parameter data by constructing a model of posterior probability, likelihood function and prior probability. The Bayesian estimation method can be used to easily approximate the real search data through the Markov chain Monte Carlo sampling method to obtain unknown data.

[0031] The above-mentioned Brownian model can be understood as the echo model of the Doppler channel. The real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay, thereby calculating the terrain height.

[0032] The above-mentioned time-delay elevation extraction process can be understood as a process of extracting information about the changes of terrain elevation over time or space from the imaging results.

[0033] The above-mentioned track direction can be understood as the flight path of a satellite or an airplane. The above-mentioned two-dimensional elevation information can be understood as the terrain features in the horizontal and vertical (ie, elevation) directions.

[0034] It should be noted that the imaging result information in the delayed Doppler map of the corrected radar imaging result can be extracted, and the imaging result information can be processed by performing elevation delay extraction by fitting the Brownian model estimation method using the Bayesian estimation method to obtain the two-dimensional elevation information of the continuous terrain along the track.

[0035] Step 102: using the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation profile and the prior information to obtain the contour point group position information; the contour point group position information and the initial reference position information are comprehensively fitted and calculated.

[0036] In the embodiment of the present invention, the above-mentioned initial reference position can be understood as the initial position provided by the current aircraft.

[0037] The digital elevation map is a digital map containing ground elevation information, usually composed of a series of regularly or irregularly distributed points, each of which records the elevation value of the ground at that location. The digital elevation map can provide prior elevation information of the ground near the flight path, which is helpful for accurate terrain matching and positioning. The digital elevation map of the current flight area is used as prior information to guide the process of searching for equal-height point sets, ensuring the accuracy and reliability of the search results.

[0038] The above-mentioned continuous elevation profile information can be understood as the continuous change of ground elevation.

[0039] The above-mentioned iso-elevation points can be understood as other points with the same or similar elevations.

[0040] Using the digital elevation map of the flight area as prior information, the two-dimensional elevation information of the continuous terrain along the track and the prior information of the digital elevation map are combined to continuously select and search for the nearest contour point with the single elevation point at the initial position as the center of the circle to obtain the position information of the contour point group. During the search process, an appropriate search range can be set, and the search range is set according to the error size. If the error is large, a larger search range needs to be set to ensure that all relevant contour points are included; conversely, if the error is small, a smaller search range can be set to improve efficiency.

[0041] It should be noted that, based on the initial reference position, the two-dimensional elevation information of the continuous terrain along the track and the prior information of the digital elevation map are used to find the nearest contour point with the initial reference position as the center of the circle, and it is recorded. All continuous contour point data are processed for contour point search, and after the processing is completed, the contour point group position information is obtained.

[0042] Step 103: When the coordinate difference loss between the contour point group position information and the initial reference position information is minimized, the contour point group position corresponding to the time when the coordinate difference loss is minimized is regarded as a new initial position.

[0043] In an embodiment of the present invention, the above-mentioned comprehensive fitting calculation may be a rigid transformation calculation. The rigid transformation calculation is a mathematical method for determining the position and direction of an object in space. The rigid transformation calculation includes rotation calculation and translation calculation.

[0044] Furthermore, the obtained position information of the contour point group is combined with the initial position information to calculate the rotation and translation. When the coordinate difference loss is the smallest, it is regarded as the best matching fitting position, which means that the current position and direction are most consistent with the position information of the contour point group.

[0045] Step 104: Based on the new initial position, the next round of continuous iso-point set search and iterative judgment of comprehensive fitting calculation is performed, and when the iterative judgment reaches the iteration termination condition, the target position is output.

[0046] The iteration termination condition refers to the number of iterations reaching a preset upper limit of the number of iterations or reaching a convergence threshold. The above-mentioned preset number of iterations is the upper limit of the number of iterations pre-defined by the system and is used to determine the iteration termination condition based on the convergence effect.

[0047] In the embodiment of the present invention, the best matching fitting position is used as a new initial position for the next round of contour point search and the initial value of rigid transformation calculation, which can improve the accuracy and efficiency of the calculation.

[0048] Furthermore, the next round of calculation is performed based on the new initial position. When the number of iterations reaches the preset upper limit of the number of iterations or the convergence threshold condition is reached, the iteration result is output, and the aircraft projection point of the selected result point set is used as the target position information.

[0049] In the embodiment of the present invention, the present invention combines the echo characteristics of the wide-beam detection radar with the flight operation environment of the aircraft, adopts the Brownian model with the Bayesian estimation method parameter fitting method, extracts the terrain contour characteristics, and according to the obtained continuous elevation contour information, cooperates with the digital elevation map prior information, performs continuous selection and search of the nearest contour point with the initial position single elevation point as the center of the circle, obtains the contour point group position information, and performs comprehensive fitting operation on the contour point group position information and the initial position information, regards the minimum coordinate difference loss as the new initial position, outputs the iteration result when the number of iterations reaches the upper limit of the number of iterations or reaches the convergence threshold condition, and selects the projection point of the result point set as the position information, so that it is suitable for the aircraft wide-beam radar terrain contour matching work. The present invention does not rely on satellite signal information, and can realize fast and accurate autonomous positioning function when the satellite signal is cut off or the signal is poor.

[0050] In an embodiment of the present invention, the imaging result information of the delayed Doppler map is obtained, and the imaging result information is subjected to elevation delay extraction processing by fitting the Brownian model using the Bayesian estimation method, so as to obtain two-dimensional elevation information of continuous terrain along the track; the initial reference position and the digital elevation map of the current flight area are obtained as prior information, and the two-dimensional elevation information of the continuous terrain along the track and the prior information of the digital elevation map are used to search for the nearest point continuous contour point set with the single elevation point of the initial reference position as the center of the circle, so as to obtain the contour point group position information; the contour point group position information and the initial reference position information are subjected to comprehensive fitting calculation, and the minimum coordinate difference loss is regarded as the new initial position; based on the new initial position, when the number of iterations reaches the preset upper limit of the number of iterations, the target position is output. The present invention can solve the problem that the traditional aircraft positioning method relies on satellite signal information, and the positioning algorithm has low computational efficiency when the satellite signal is cut off or the signal is poor, thereby realizing a fast and accurate autonomous positioning function when the satellite signal is cut off or the signal is poor.

[0051] It is understandable that in the specific implementation of this application, data related to robot data, home device data, task data, etc. are involved. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data, as well as the training, deployment and calling of large language models, must comply with relevant laws, regulations and standards of relevant countries and regions.

[0052] Optionally, the Brownian model expression is as follows:

[0053] Represents the mathematical parameter echo model Brownian model, referred to as Brownian model, where represents the planar impulse response of the delay-Doppler map, Indicates echo delay, which means the time it takes for a signal to be transmitted and received. represents the frequency of the delay-Doppler map, It describes the scattering characteristics of the detection surface when the altimeter echo is illuminated nearly vertically by integrating a suitable function on a circle. The probability density function of the plane scattering intensity representing the delay-Doppler map, represents the transmission probability of the delay-Doppler map.

[0054] In the embodiment of the present invention, the Brownian model is the echo model of each Doppler channel, and the real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay, thereby calculating the terrain height. The Brownian model can be a three-term convolution model.

[0055] The planar impulse response of the above delay-Doppler pattern is Depends only on time echo delay , which is obtained by integrating the illuminated area of ​​the surface. It is obtained by integrating a suitable function over a circle whose radius depends on time.

[0056] The planar impulse response of the above delay-Doppler pattern is Describes the system's response to a pulse signal at a certain time point and frequency.

[0057] The plane scattering intensity probability density function of the above delay Doppler map is Describes the probability distribution of the scattering intensity at a given time or location.

[0058] The transmission probability of the above delay-Doppler map is It represents the probability that a signal can be successfully transmitted to the receiver at a certain point in time and frequency.

[0059] Optional, The expression is as follows:

[0060] in, Indicates the echo delay, represents the plane spatial position of the delay Doppler map, represents the amplitude value of the delay Doppler image, represents the exponential term of the delay-Doppler map, The function representing the delay-Doppler map, represents the difference term of the delay-Doppler map; and and The relevant angle is defined as:

[0061] in, represents the radius of the circle, Representing coordinates The integral of Representing coordinates 's points.

[0062] In an embodiment of the present invention, is obtained by integrating a suitable function over a circle with the radius Depends on time. and Coordinates Integrate into rectangular beams.

[0063] Optional, The expression is as follows:

[0064] in, Indicates the echo delay, represents the standard deviation, , Indicates the average height value.

[0065] In the embodiment of the present invention, the delay Doppler map Usually approximated by a Gaussian density, its standard deviation (STD) is similar to the average height value The above Gaussian density is used to approximately describe the probability distribution of random variables. The probability distribution of random variables can be approximated as Gaussian distribution, that is, normal distribution.

[0066] Optional, The expression is as follows:

[0067] in, Indicates the echo delay, is the sampling period, is the altimeter receiving bandwidth, To delay the acquisition time of the Doppler image, represents the frequency of the delay-Doppler map, is the sampling frequency.

[0068] In the embodiment of the present invention, the radar system It is approximated by a square cardinality. The square cardinality is the square value of a number. For example, if the cardinality is 2, then the square of the cardinality is 4.

[0069] Optionally, the Bayesian estimation method is used to fit the Brownian model to perform single elevation time-delay extraction processing on the imaging result information, and to extract the elevation gradient information of the continuous elevation profile, specifically: The posterior probability is constructed using the Bayesian expression, and the expected value of the posterior probability is calculated to obtain the echo delay. Estimated results; is the echo delay, which indicates the time from signal transmission to reception. The corresponding terrain height is calculated according to the echo delay to obtain the single elevation delay extraction processing result; Accumulate the results of multiple single elevation delay extraction processes to obtain continuous elevation contour elevation values; The obtained continuous elevation profile elevation values ​​are averaged to obtain the elevation mean of the continuous elevation profile, and then the elevation mean is subtracted from the continuous elevation profile elevation value to obtain the elevation gradient information of the continuous elevation profile.

[0070] The above Bayesian estimation method is a probabilistic statistical method, which calculates the best parameter data by constructing a model of posterior probability, likelihood function and prior probability. The Bayesian estimation method can be used to easily approximate the real search data through the Markov chain Monte Carlo sampling method to obtain unknown data.

[0071] The Bayesian expression is as follows:

[0072] in, , and They represent the posterior probability, likelihood function and prior probability (i.e., the prior probability of the hidden variable), respectively. is the observed data, is the echo delay, is the hidden random variable, and the likelihood function and the prior probability are combined to construct the posterior distribution. In the above expression, the prior probability refers to the prior probability of the hidden random variable, and the likelihood function and the prior probability are combined to construct the posterior probability. Once the posterior probability is obtained , the result echo delay The estimated result is calculated by calculating the posterior probability The expected value of is obtained. , the terrain height can be calculated accordingly. Therefore, it is very important to choose a suitable probability model in the Bayesian framework.

[0073] Sparse distributions such as Laplace are often used as priors To be applied in Bayesian inference

[0074] Represents a hyperparameter.

[0075] The likelihood function can be defined as:

[0076] is the noise variance, and its distribution is:

[0077] follows an inverse gamma prior distribution, which is conjugate to the Gaussian distribution of the likelihood.

[0078] The Laplace distribution is used as a sparse prior, but it is not conjugate with the Gaussian distribution in the likelihood function, so a hierarchical approach is used. The first layer is:

[0079] represents the hyperparameters in the Gaussian distribution. In the second layer, the hyperparameters is further constrained by a gamma distribution.

[0080]

[0081] It is conjugated with the Gaussian distribution in the likelihood function, and the resulting marginal prior Follow the The expected Laplace distribution of the distribution when . Yes Control Hyperparameter for sparsity.

[0082] At this point, the posterior probability density can be calculated. Its expression is as follows:

[0083] The Markov chain Monte Carlo sampling method is applied to sample the posterior distribution. Each random variable and hyperparameter can be obtained in the form of a closed solution, including the parameter Echo delay.

[0084] Get elevation parameters After that, the gradient information is extracted. The continuous elevation profile is averaged to obtain the elevation mean, and then the elevation mean is subtracted from the elevation value of the continuous elevation profile to obtain the elevation gradient information of the continuous elevation profile.

[0085] Optionally, a digital elevation map of the current flight area and the initial reference position are used as prior information, and a continuous contour point set search is performed based on the elevation gradient information and prior information of the continuous elevation contour, specifically including: Get the pre-selected digital elevation map of the current flight area in advance; The pre-selected digital elevation map is delineated, and the delineated range is adjusted accordingly according to the initial position and its irradiated area; the endpoint of the irradiated area is used as the reference position, and the extended area of ​​the preset size is determined as the pre-selected range of the area according to factors such as the size of the irradiated range, and the pre-selected area range of the current area is delineated; Based on the pre-selected area, the elevation gradient information of the digital elevation map of the pre-selected area is extracted to obtain the prior information; A continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the elevation gradient information of the pre-selected area. That is, for each elevation point of the continuous elevation contour gradient, the nearest contour point search is performed in the pre-selected area to obtain the contour point group information.

[0086] This step can reduce the amount of calculation and improve positioning accuracy to a certain extent by delineating the pre-selected area.

[0087] The method of extracting the elevation gradient information of the digital elevation map in the preselected area is as follows: calculating the average elevation value of the digital elevation map of the preselected area; subtracting the calculated average elevation value of the digital elevation map of the preselected area from all elevation values ​​of the preselected area to obtain the elevation gradient information index of the preselected area in the current area.

[0088] In the embodiment of the present invention, the digital elevation map is a digitized map containing ground elevation information, which is usually composed of a series of regularly or irregularly distributed points, each of which records the elevation value of the ground at that location. The digital elevation map can provide a priori elevation information of the ground near the flight path, which is helpful for accurate terrain matching and positioning.

[0089] Specifically, the digital elevation map matching area within the positioning error range is delineated for the digital elevation map. The delineation range is adjusted accordingly according to the initial reference position of the aircraft and its irradiation area. The pre-selected area is matched and extended in the geometric direction based on the endpoints of the irradiation area along the track to the position of the maximum theoretical error to complete the delineation of the current flight area. The endpoints of the flight irradiation area are used as the reference position, and a certain size of the extension area is determined as the pre-selected area according to factors such as the size of the irradiation range. This step can reduce the amount of calculation to a certain extent and improve positioning accuracy.

[0090] Optionally, the position information of the contour point group includes the center position of the point set and the coordinate difference between each point and the center, wherein the coordinate difference between each point and the center is expressed as: ,

[0091] in, is the iso-height point of the delay-Doppler map, is the initial reference position of the delay Doppler map, are the center coordinates of the isoheight points of the delay-Doppler map, is the center coordinate of the initial reference position of the delay Doppler map, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

[0092] Optionally, the principles followed by the iso-height point set search process are the Euclidean distance and the minimum principle. The Euclidean distance and expression are as follows:

[0093] In the formula, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation, including rotation and translation transformation , is the total number of points;

[0094] in, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation translation, is the rigid transformation rotation, The total number of points.

[0095] In the embodiment of the present invention, the Euclidean distance is the straight-line distance between two points, which is used to evaluate the similarity between point sets. The smaller the distance, the higher the similarity.

[0096] The above rigid transformation translation can be understood as the linear movement distance from one point set to another point set, indicating the relative position change of the point set. The above rigid transformation rotation can be understood as the rotation angle from one point set to another point set, indicating the relative angle change of the point set.

[0097] Optionally, the Euclidean distance expression is as follows:

[0098] in, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

[0099] In an embodiment of the present invention, the present invention can train iterative operations until the number of iterations reaches an upper limit or a convergence threshold condition is reached, output the iteration result, and select the projection point of the result point set as the target position information.

[0100] like Figure 2 As shown, Figure 2 FIG. 1 is a flow chart of a radar terrain contour matching positioning method provided by another embodiment of the present invention. Specifically, it includes steps 200 to 207: Step 200: pre-processing of radar echoes.

[0101] Among them, after the radar altimeter receives the backscattered signal from the ground, it will obtain the processed delayed Doppler map after full de-skewing, intermediate frequency filtering, FFT transformation and other processing.

[0102] Step 201: Brownian model construction.

[0103] Among them, the Brownian model is the echo model of each Doppler channel. The real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay, thereby calculating the terrain height. The Brownian model can be a three-term convolution model.

[0104] Step 202: Brownian model fitting and elevation parameter acquisition.

[0105] Among them, the imaging result information in the delayed Doppler map of the corrected radar imaging result is extracted, and the elevation delay of each channel is extracted by fitting the Brownian model estimation method using the Bayesian estimation method. The elevation is calculated based on the delay to obtain the two-dimensional elevation information of the continuous terrain along the track. The above-mentioned Bayesian estimation method is a probabilistic statistical method. It calculates the optimal parameter data by constructing a model of posterior probability, likelihood function and prior probability. The Bayesian estimation method can be used to easily approximate the real search data through the Markov chain Monte Carlo sampling method to obtain unknown data.

[0106] Step 203: Pre-select matching area.

[0107] Among them, the digital elevation map of the flight area is used as prior information, the initial position provided by the current aircraft is used as the initial reference position for matching, and a certain area range is extended with the initial reference position as the center to complete the delineation of the matching area.

[0108] Step 204: search for equal height points.

[0109] Among them, the digital elevation map of the flight area is used as prior information. According to the obtained continuous elevation contour information and the digital elevation map prior information, a continuous selection search process is carried out with the nearest equal elevation point as the center of the circle at the initial position single elevation point. During the search process, an appropriate search range needs to be set, and the search range is set according to the error size.

[0110] Step 205: Calculate rigid transformation.

[0111] Among them, the position information of the contour point group and the initial position information are subjected to a comprehensive fitting operation, including rotation and translation operations. The position with the smallest coordinate difference loss is regarded as the best matching fitting position, and this position is used as the new initial position for the next round of contour point search and the initial value of rigid transformation calculation.

[0112] Step 206: Determine whether convergence has occurred.

[0113] Wherein, two iteration termination conditions are specified: the upper limit of the number of iterations and the judgment of the convergence effect. When the number of iterations reaches the upper limit of the number of iterations or reaches the convergence threshold condition, the process proceeds to step 207; otherwise, the process proceeds to step 204.

[0114] Step 207: Positioning result.

[0115] Among them, when the number of iterations reaches the upper limit of the number of iterations or the convergence threshold condition is reached, the iteration result is output, and the aircraft projection point of the result point set is selected as the aircraft position information to complete the final positioning work.

[0116] In the embodiment of the present invention, the present invention combines the echo characteristics of the wide beam detection radar with the flight operation environment of the aircraft, adopts the Brownian model with the Bayesian estimation method parameter fitting method, extracts the terrain contour characteristics, and according to the obtained continuous elevation contour information, cooperates with the digital elevation map prior information, performs continuous selection and search of the nearest contour point with the initial position single elevation point as the center of the circle, obtains the contour point group position information, and performs comprehensive fitting operation on the contour point group position information and the initial position information, regards the minimum coordinate difference loss as the new initial position, outputs the iteration result when the number of iterations reaches the upper limit of the number of iterations or reaches the convergence threshold condition, and selects the projection point of the result point set as the position information, so that it is suitable for the aircraft wide beam radar terrain contour matching work. The present invention can realize the function of fast and accurate autonomous positioning when the satellite signal is cut off or the signal is poor.

[0117] like Figure 3 As shown, Figure 3 It is a model diagram of the radar terrain contour matching positioning method provided by an embodiment of the present invention. Specifically, the radar wide beam is irradiated to the three-dimensional terrain, and based on the echo energy distribution characteristics, two-dimensional continuous terrain information is obtained across dimensions, and the gradient extraction of the digital elevation map elevation and the extracted elevation is completed. The present invention fits the echo of each channel to the Brownian echo model, and the extraction process is to fit the Brownian model with the Bayesian estimation method to perform height extraction.

[0118] The present invention improves the traditional ICCP positioning algorithm, enhances the adaptability of the algorithm, and uses a Brownian model-based elevation profile extraction method based on the characteristics of radar echo delay Doppler map data. In addition, in view of the low computational efficiency of the traditional ICCP positioning algorithm and other aircraft positioning algorithms, the present invention adopts relevant strategies to reduce the algorithm computational complexity and optimize the algorithm iteration logic.

[0119] like Figure 4 As shown, Figure 4It is a Brownian model signal diagram provided by an embodiment of the present invention. Specifically, after the radar altimeter receives the backscattered signal from the ground, it will obtain a processed delayed Doppler map after full de-skewing, intermediate frequency filtering, FFT transformation and other processing. The delay of the delayed Doppler map corresponds to the height between the aircraft and the ground. The Brownian model is the echo model of each Doppler channel. The real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay, thereby calculating the terrain height. The Brownian model can be a three-term convolution model.

[0120] like Figure 5 As shown, Figure 5 It is a schematic diagram of matching area preselection provided by an embodiment of the present invention. Specifically, in order to speed up the operation speed of iterative positioning calculation and improve the work efficiency of iterative calculation, the digital elevation map matching area within the positioning error range can be delineated for the digital elevation map, and the delineated range is adjusted accordingly according to the original initial position of the aircraft and its irradiation area, and is extended in the geometric direction based on the endpoint of the irradiation area along the track to the position of the maximum theoretical error. Among them, P represents the irradiation area, A represents the angle of the irradiation area relative to the DEM map, W represents the extension distance perpendicular to the irradiation area, and L represents the extension distance along the irradiation area, and finally forms the irradiation area represented by the extended solid line.

[0121] like Figure 6 As shown, Figure 6 : is a schematic diagram of matching positioning provided by an embodiment of the present invention. Specifically, by adopting a wide-beam radar illumination elevation extraction method, a number of continuous elevation values ​​can be obtained at one time, and multi-point one-time fast matching is adopted, without waiting for the accumulation of elevation points, so that the matching process has higher computational efficiency. Among them, X represents the actual position point, TP represents the matching position point, P represents the initial reference position point, and C represents the contour line of the map.

[0122] like Figure 7-Figure 9 As shown, Figure 7 is a simulated terrain scene map provided by an embodiment of the present invention, Figure 8 is a delay Doppler map provided by an embodiment of the present invention, Fig. 9 is an elevation extraction result map provided by an embodiment of the present invention, Fig.10 is a matching positioning result diagram provided by an embodiment of the present invention. Specifically, a simulation experiment can be conducted on the present invention. The simulation conditions are:

[0123] When the initial error is 50 meters, after Brownian model elevation extraction and ICCP iterative matching processing, after 100 rapid iterations, the positioning accuracy can reach various orders of magnitude. The positioning accuracy of the present invention depends on the accuracy of extracted terrain and the accuracy of simulated digital elevation maps. The present invention has high reliability. For the situation of inaccurate extraction of individual elevation points, the present invention is able to reduce the negative impact of individual bad value points, and the overall algorithm computational complexity is small, and has a broad prospect for engineering application.

[0124] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0125] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A radar terrain contour matching positioning method, characterized in that: The method comprises the following steps: The wide beam of the radar is irradiated toward the three-dimensional terrain to obtain the imaging result information of the delayed Doppler map, and the Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and the elevation gradient information of the continuous elevation contour is extracted; Taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation profile and the prior information to obtain contour point group position information; the contour point group position information and the initial reference position information are comprehensively fitted and calculated; When the coordinate difference loss between the position information of the contour point group and the initial reference position information is minimized, the position of the contour point group corresponding to the time when the coordinate difference loss is minimized is regarded as a new initial position; Based on the new initial position, the next round of continuous isohelite point set search and iterative judgment of comprehensive fitting calculation is performed, and when the iterative judgment reaches the iteration termination condition, the target position is output.

2. The radar terrain profile matching positioning method according to claim 1, characterized in that: The Brownian model expression is as follows: , represents the Brownian model, where is the planar impulse response of the delay-Doppler map; It is the echo delay, which indicates the time from signal transmission to reception; is the frequency of the delay Doppler map; It is achieved by integrating a specified function on a circle and is used to describe the scattering characteristics of the detection surface when the altimeter echo is illuminated nearly vertically. The probability density function of the plane scattering intensity representing the delay-Doppler map; represents the transmission probability of the delay-Doppler map.

3. The radar terrain profile matching positioning method according to claim 2, characterized in that: Said The expression is as follows: in, Indicates the echo delay, represents the plane spatial position of the delay Doppler map, represents the amplitude value of the delay Doppler image, represents the exponential term of the delay-Doppler map, The function representing the delay-Doppler map, represents the difference term of the delay-Doppler map.

4. The radar terrain profile matching positioning method according to claim 2, characterized in that: Said The expression is as follows: in, Indicates the echo delay, represents the standard deviation, , Represents the average height value, Represents the speed of light.

5. The radar terrain profile matching and positioning method according to claim 2, characterized in that: Said The expression is as follows: in, Indicates the echo delay, is the sampling period, is the altimeter receiving bandwidth, To delay the acquisition time of the Doppler image, represents the frequency of the delay-Doppler map, is the sampling frequency.

6. The radar terrain profile matching positioning method according to claim 1, characterized in that: The Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and to extract elevation gradient information of continuous elevation contours, specifically: The posterior probability is constructed using the Bayesian expression, and the expected value of the posterior probability is calculated to obtain the echo delay. Estimated results; is the echo delay, which indicates the time from signal transmission to reception. The corresponding terrain height is calculated according to the echo delay to obtain the single elevation delay extraction processing result; Accumulate the results of multiple single elevation delay extraction processes to obtain continuous elevation contour elevation values; The obtained continuous elevation profile elevation values ​​are averaged to obtain the elevation mean of the continuous elevation profile, and then the elevation mean is subtracted from the continuous elevation profile elevation value to obtain the elevation gradient information of the continuous elevation profile.

7. The radar terrain profile matching and positioning method according to claim 1, characterized in that: Taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the prior information, specifically including: Get the pre-selected digital elevation map of the current flight area in advance; The pre-selected digital elevation map is delineated, and the delineated range is adjusted accordingly according to the initial position and the irradiated area; the endpoint of the irradiated area is used as a reference position, and an extended area of ​​a preset size is determined as the range of the pre-selected area, thereby completing the delineation of the pre-selected area of ​​the current area; Based on the preselected area, extracting the elevation gradient information of the digital elevation map of the preselected area, that is, obtaining the prior information; The continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the elevation gradient information of the preselected area to obtain the contour point group information.

8. The radar terrain profile matching and positioning method according to claim 1, characterized in that: The position information of the contour point group includes the center position of the point set and the coordinate difference between each point and the center, wherein the coordinate difference between each point and the center is expressed as: , in, is the iso-height point of the delay-Doppler map, is the initial reference position of the delay Doppler map, are the center coordinates of the isoheight points of the delay-Doppler map, is the center coordinate of the initial reference position of the delay Doppler map, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

9. The radar terrain profile matching positioning method according to claim 8, characterized in that: The continuous search of the iso-height point set follows the Euclidean distance and minimum principle. The Euclidean distance and expression are as follows: In the formula, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation, including rotation and translation transformation , is the total number of points; in, Point Set Each point in , After rigid transformation The processed point set Points, is the rigid transformation translation, is the rigid transformation rotation, The total number of points.

10. The radar terrain profile matching positioning method according to claim 9, characterized in that: The Euclidean distance expression is as follows: in, is the coordinate difference between the iso-height point and the center of the delay Doppler map, is the difference between the initial reference position and the center coordinate of the delay Doppler map.

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